BC xiaozhi-math-concept-explainer
初中数学概念的理解与重建：学生不是卡在某道题，而是卡在"这个数学概念本身没懂"时用。典型触发："这个数学公式我知道但不明白为什么""负负为什么得正""一次函数和正比例有什么区别""几何题我脑子里建不起图形""这两个数学概念我总是混""用生活例子讲讲这个概念"。核心方法：三种解释模型（生活类比 / 图解可视化 / 逐步拆分）+ 几何空间想象训练。不处理：具体某道题怎么做（转 xiaozhi-math-problem-solving-coach）、应用题列式（转 xiaozhi-math-word-problem-coach）、错题收录与统计（转 xiaozhi-correction-notebook）、分层进阶练习（转 xiaozhi-math-gradient-trainer）。
初中数学概念的理解与重建：学生不是卡在某道题，而是卡在"这个数学概念本身没懂"时用。典型触发："这个数学公式我知道但不明白为什么""负负为什么得正""一次函数和正比例有什么区别""几何题我脑子里建不起图形""这两个数学概念我总是混""用生活例子讲讲这个概念"。核心方法：三种解释模型（生活类比 / 图解可视化 /…
As a process C 53/100 · Has gaps — weak spots: result and completion, when it triggers, inputs and preconditions
How to improve
- Say in the description WHEN to use the skill ("use when…", example requests): that is the agent's main cue.
- For Hermes the description must be one sentence under 60 characters; move the conditions to a "When to Use" section.
- Your own cases (evals/evals.json, 4–6 real requests with expected answers): the full check would then run those instead of a model-drafted suite.
- A spec.yaml with trigger phrases and assertions — a behaviour contract for CI; `skilltest init` writes a template.
Guard findings · 0
✓ No critical or high findings
Files scanned: 10. Evidence is masked. Grey chips explain why severity was lowered.
Against the Agent Skills spec
- warning
description-long-hermesdescription is 344 chars; the Hermes authoring standard requires ≤ 60 (one sentence, ending with a period) - warning
description-no-whenneither description nor a "## When to Use" section says when to use the skill - note
frontmatter-keyunknown frontmatter key "display_name" - note
frontmatter-keyunknown frontmatter key "grade_bands" - note
frontmatter-keyunknown frontmatter key "depends_on" - note
frontmatter-keyunknown frontmatter key "slug" - note
frontmatter-keyunknown frontmatter key "displayName" - note
frontmatter-keyunknown frontmatter key "summary"
Process rating: all ten parameters 53/100
- 0Result and completion. Does not say what the result is
- 0Inputs and preconditions. Does not say what the process needs to start
- 0Failures and branches. Linear process with no failure handling
- 0Progress reporting. Says nothing while it works
- 20When it triggers. No condition that starts the skill
- 100Tools and files. No external tools needed
- 100Steps. 5 steps
- 100Consistency. Name and required fields are in place
- 100Execution cost. Instruction body is 1332 tokens
- 100Running it twice. No mutating operations
Everything here is measured from the skill text rather than judged by a model, so the numbers are checkable. A parameter weighs more when it is a more common reason for the process to stall.
Quality signals
- +4Description does not say when NOT to use the skill (false activations)
- +3Output format is not stated: the model decides each time
- +2Single-language instructions
- +5Description quotes 7 example trigger phrases
- +3Description length 344: enough signal without eating the budget
- +4Structure: 18 headings
- +3Step-by-step instructions: 5 items
- +4Has examples (19 code blocks)
- +4Reference files are cited in the instructions (1 of 1)
- +1License stated
Quality base 70; lint remarks subtract, signals add up to 100. Result: 73.